So, your hearing a lot regarding semantics nowadays! “The best way to get search engine traffic is to be on top in semantic SEO” is often a quote stated by many digital marketers. But, What is semantic search and how does semantic SEO impact your digital marketing strategy? Let’s analyze.
Table of Contents
What is Semantic Search?
Semantic search is defined as the ability of search engines to understand the intent and contextual meaning of content published on various sources online and fetch it to respective search phrases generated by users on the web.
If we time travel, there was a time when search engines could only analyze for specific search terms/phrases in a content copy. Now, search engine algorithms are more sophisticated and carry the power to incorporate semantic search principles when ranking content for respective positions.
What are ‘Semantic Principles’?
Broadly, there are two primary factors used for defining semantic search,
- Search intent of the user. Search intent (or also known as keyword intent) is the reason why someone performs a search query. It relates to what the user is seeking via conducting a search query, or simply, trying to accomplish on search engines. Search intent can be classified to learn, to find, or to buy something. By evaluating the intent of the query, search engines can provide more relevant results (e.g., answer to a question, a brand’s website, a product page, etc.)
- Semantic meaning of search queries. Fundamentally, the term ‘semantic’ refers to the study of meaning and relationships between words. In the world of search engines, semantics relates to the relationships between queries, the phrases, and words related to it, and lastly, the content on webpages.
By considering semantics (what the words mean, not just what they are), search engines can display results that are more closely related to the context of the search query.
Importance of Semantic Search (& the History)
In order to understand the semantic search, you first need to learn about its history. In the early age of search engines, keywords were the primary ranking factor. Ideally, more the prominence of a specific keyword on a webpage, higher was the rank in search engines.
When search engines first started, keywords were the main ranking factor. Usually, a page that repeated the target search term the most times would get top placement on search engine results pages (SERPs). As it was easy to manipulate, the system was not widely adopted.
Also, old search engine systems were difficult for end users as well as they could not find relevant information for search queries.
This was primarily due to the fact as search engines couldn’t decipher the meaning & context of search engines. They could only analyze & produce exact match results on a specific query.
Semantic search benefitted both end users and search engines as,
- It made it difficult for spammers to employ black hat SEO for manipulating search results and helped in cutting down low-quality content.
- It made search results more intuitive, which helped users find results which were more relevant to their queries.
A few Other Factors
As search engines continue to progress with algorithms, improvising their results, and delivering better experiences for their users, there are three other factors to one should consider:
- Featured snippets & rich snippet results
- RankBrain & Hummingbird
- Voice search results
Featured Snippets and Rich Results
Knowledge Graph made its debut in 2012 and was introduced to help users “discover new information quickly & easily.”
In Knowledge Graph, search engines leverage semantic search to decipher the meaning of the query and deliver as accurate results as possible. After its debut, Google has made its shift towards providing answers directly through SERPs. In 2019, Google can display content from various web pages as Knowledge Graph results, featured snippets, rich results to deliver more prominent and accurate results to users.
Knowledge Graph Search Result
Featured Snippet Search Result
Rich Search Result
Hummingbird & RankBrain
As Google progresses in refining its search engine algorithm, it constantly is introducing updates and adding ranking factors to its algorithms to make search better and more accurate.
In 2013, Google introduced the Hummingbird algorithm which carried the emphasis on principles of semantic search and a combination of natural language queries.
Moving forward, in 2015, Google release RankBrain, which made use of artificial intelligence to analyze and learn about the best-performing search results. Both the updates, together, moved the benchmark of the search industry forward.
Another wave which is changing the user behavior on search engines is the voice search. As more and more people are speaking their search queries to virtual assistants like Google Home, Alexa, and Apple Siri, search engines are evolving to recognize the conversational and semantic nature of search queries.
Few pieces of research show that voice searches employ the use of more natural language, longer search phrases, and complex question. To serve with the best results, search engines have to rely heavily on search principles to deliver precise results to these types of results.
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